Identifying patterns of depression in the elderly through data mining
DOI:
https://doi.org/10.59681/2175-4411.v16.2024.1020Keywords:
Depression, Data Mining, Machine LearningAbstract
Objective: Identify patterns of depression in elderly people based on exogenous variables through data mining. Methods: The process applies the Random Forest classification technique to describe the patterns of depression in this population. The PNS, IBGE 2013 database is considered as a data source. Results: The results highlight pre-existing chronic diseases, level of trust with friends and relatives, level of education, etc. as relevant factors. For the group diagnosed “With depression”, the accuracy of the model was 68.8%, sensitivity of 77.2% and F1-score measurement of 72.8%. For the group diagnosed “No depression”, the accuracy was 66.4%, Sensitivity was 56.2% and the F1-score measure was 60.9%. Conclusion: Among the factors that stand out, in terms of importance, are pre-existing chronic illness, one or no relatives or friends to trust, and education up to high school. Practicing physical exercise and staying active is a favorable aspect for non-depression.
References
Maier A, Riedel-Heller SG, Pabst A, Luppa M. Risk factors and protective factors of depression in older people 65+. A systematic review. PLoS One. 2021 May 13;16(5):e0251326. DOI: https://doi.org/10.1371/journal.pone.0251326
Lelis KCG, Brito RVNE, Pinho S, Pinho L. Sintomas de depressão, ansiedade e uso de medicamentos em universitários. Revista Portuguesa de Enfermagem de Saúde Mental. 2020; 23:9-14.
Lopez AD, Mathers CD. Measuring the global burden of disease and epidemiological transitions: 2002-2030. Ann Trop Med Parasitol. 2006 Jul-Sep;100(5-6):481-99. DOI: https://doi.org/10.1179/136485906X97417
Andrade ABCA, Ferreira AA, Aguiar MJ. Conhecimento dos idosos sobre os sinais e sintomas da depressão. Saúde Redes. 2016;2(2):157-166. DOI: https://doi.org/10.18310/2446-4813.2016v2n2p157-166
Sousa KA, Freitas FFQ, Castro AP, Oliveira CDB, Almeida AAB, Sousa KA. Prevalência de sintomas de depressão em idosos assistidos pela Estratégia de Saúde da Família. Rev Mineira de Enferm. 2017;21:e-1018.
Soares ThD, Peroza LR, Cerezer M, Nedel Sh.S, Branco JC. Efeitos do exercício físico na obesidade e depressão: uma revisão. Rev. Bras. de Obesidade, Nutrição e Emagrecimento. 2020;14(86):511-518.
Zwolińska W, Dmitrzak-Węglarz M, Słopień A. Biomarkers in Child and Adolescent Depression. Child Psychiatry Hum Dev. 2023 Feb;54(1):266-281. Epub 2021 Sep 29. PMID: 34590201; PMCID: PMC9867683. DOI: https://doi.org/10.1007/s10578-021-01246-y
Peluso ETP, Blay SL. Percepção da depressão pela população da cidade de São Paulo. Rev. Saúde Pública. 2008;42(1):41-48. DOI: https://doi.org/10.1590/S0034-89102008000100006
Ferreira PCS, Martins NPF, Rodrigues LR, Ferreira LA. Características sociodemográficas e hábitos de vida de idosos com e sem indicativo de depressão. Rev Eletrônica de Enfermagem. 2013;15(1):197-204. DOI: https://doi.org/10.5216/ree.v15i1.16643
Benedetti TRB, Borges LJ, Petroski EL, Gonçaçves LHT. Atividade física e estado de saúde mental de idosos. Rev Saúde Pública. 2008;42(2):302-307. DOI: https://doi.org/10.1590/S0034-89102008005000007
Tier CG, Lunardi VL, Santos SSC. Cuidado ao idoso deprimido e institucionalizado à luz da Complexidade. Rev. Elet. Enferm. 2008;10(2):530-536. DOI: https://doi.org/10.5216/ree.v10i2.8065
Dipnall JF, Pasco JA, Berk M, Williams LJ, Dodd S, Jacka FN. Fusing Data Mining, Machine Learning and Traditional Statistics to Detect Biomarkers Associated with Depression. PLoSONE. 2016;11(2): e0148195. DOI: https://doi.org/10.1371/journal.pone.0148195
Oh J, Yun K, Maoz U, Kim T-S, Chae J-H. Identifying depression in the National Health and Nutrition Examination Survey data using a deep learning algorithm. Journal of Affective Disorders. 2019;257:623-631. DOI: https://doi.org/10.1016/j.jad.2019.06.034
Montevecchi ALD, Zárate LE. PICTOREA: Um método para descoberta de conhecimento em banco de dados convencionais. Novas Edições Acadêmicas; 2014, 104 p.
Brasil. Instituto Brasileiro de Geografia e Estatística -IBGE. PNS – Pesquisa Nacional de Saúde; 2013. [Citado 2024 jun 24]. Disponível em: https://www.ibge.gov.br/estatisticas/sociais/justica-e-seguranca/29540-2013-pesquisa-nacional-de-saude.html?=&t=resultados.
Esmaily H, Tayefi M, Doosti H, Ghayour-Mobarhan M, Nezami H, Amirabadizadeh A. A Comparison between Decision Tree and Random Forest in Determining the Risk Factors Associated with Type 2 Diabetes. J Res Health Sci. 2018 Apr 24;18(2):412.
Batista GEAPA, Prati RC, Monard MC. 2004. A study of the behavior of several methods for balancing machine learning training data. SIGKDD Explor. Newsl. 6, 1 (June 2004), 20–29. DOI: https://doi.org/10.1145/1007730.1007735
Zarate L, Petrocchi B, Maia CD, Felix C, Gomes MP. CAPTO - A method for understanding problem domains for data science projects. 23(15):922-41. DOI: https://doi.org/10.53660/CLM-1815-23M33
Brito VCA, Bello-Corassa R, Stopa SR, Sardinha LMV, Dahl CM, Viana MC. Prevalência de depressão autorreferida no Brasil: Pesquisa Nacional de Saúde 2019 e 2013. Epidemiologia e Serviços de Saúde v. 31, n. spe1, e2021384. DOI: https://doi.org/10.1590/ss2237-9622202200006.especial
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Luis Enrique Zárate, Arthur Vinicius do Carmo Santos, Jefferson Eduardo de Carvalho Camelo, Cristiane Neri Nobre, Mark Alan Junho Song
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Submission of a paper to Journal of Health Informatics is understood to imply that it is not being considered for publication elsewhere and that the author(s) permission to publish his/her (their) article(s) in this Journal implies the exclusive authorization of the publishers to deal with all issues concerning the copyright therein. Upon the submission of an article, authors will be asked to sign a Copyright Notice. Acceptance of the agreement will ensure the widest possible dissemination of information. An e-mail will be sent to the corresponding author confirming receipt of the manuscript and acceptance of the agreement.
